eprintid: 583
rev_number: 15
eprint_status: archive
userid: 10
dir: disk0/00/00/05/83
datestamp: 2012-10-29 16:08:06
lastmod: 2015-05-29 20:12:20
status_changed: 2012-10-29 16:08:06
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Poppe, K
creators_name: Bouwe van den Berg, J
creators_name: Blank, E
title: Thruster Allocation for Dynamical Positioning
ispublished: pub
subjects: environment
subjects: utilities
subjects: discrete
subjects: transport
studygroups: esgi72
companyname: Maritime Research Institute, Netherlands
full_text_status: public
abstract: Positioning a vessel at a fixed position in deep water is of great importance when working offshore. In recent years a Dynamical Positioning (DP) system was developed at Marin [2]. After the measurement of the current position and external forces (like waves, wind etc.), each thruster of the vessel is actively controlled to hold the desired location.
In this paper we focus on the allocation process to determine the settings for each thruster that results in the minimal total power and thus fuel consumption. The mathematical formulation of this situation leads to a nonlinear optimization problem with equality and inequality constraints, which can be solved by applying Lagrange multipliers.
We give three approaches: first of all, the full problem was solved using the MATLAB fmincon routine with the solution from the linearised problem as a starting point. This implementation, with robust handling of the situations where the thrusters are overloaded, lead to promising results: an average reduction in fuel consumption of approximately two percent. However, further analysis proved useful. A second approach changes the set of variables and so reduces the number of equations. The third and last approach solves the Lagrange equations with an iterative method on the linearized Lagrange problem.
date: 2010
citation:   Poppe, K and Bouwe van den Berg, J and Blank, E  (2010) Thruster Allocation for Dynamical Positioning.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/583/1/Amst103.pdf